This pipeline computes the correlation between significant copy number variation (cnv) genes and selected clinical features.
Testing the association between copy number variation of 39 peak regions and 2 clinical features across 48 patients, no significant finding detected with Q value < 0.25.
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No gene cnvs related to clinical features.
Table 1. Get Full Table Overview of the association between significant copy number variation of 39 regions and 2 clinical features. Shown in the table are P values (Q values). Thresholded by Q value < 0.25, no significant finding detected.
|
Clinical Features |
VITALSTATUS | GENDER | ||
| nCNV (%) | nWild-Type | Fisher's exact test | Fisher's exact test | |
| Amp Peak 1(1q22) | 36 (75%) | 12 |
1 (1.00) |
0.176 (1.00) |
| Amp Peak 2(2p24 1) | 16 (33%) | 32 |
0.359 (1.00) |
0.535 (1.00) |
| Amp Peak 3(3q26 31) | 9 (19%) | 39 |
0.461 (1.00) |
1 (1.00) |
| Amp Peak 4(4q13 3) | 10 (21%) | 38 |
0.0723 (1.00) |
0.487 (1.00) |
| Amp Peak 5(5p15 33) | 19 (40%) | 29 |
0.556 (1.00) |
1 (1.00) |
| Amp Peak 6(5q31 1) | 18 (38%) | 30 |
0.371 (1.00) |
0.762 (1.00) |
| Amp Peak 7(6p21 1) | 17 (35%) | 31 |
1 (1.00) |
0.762 (1.00) |
| Amp Peak 8(6q12) | 10 (21%) | 38 |
0.724 (1.00) |
0.487 (1.00) |
| Amp Peak 9(7q21 2) | 15 (31%) | 33 |
1 (1.00) |
0.064 (1.00) |
| Amp Peak 10(8q24 13) | 28 (58%) | 20 |
0.142 (1.00) |
0.245 (1.00) |
| Amp Peak 11(11q13 3) | 7 (15%) | 41 |
0.416 (1.00) |
0.687 (1.00) |
| Amp Peak 12(13q32 3) | 10 (21%) | 38 |
0.724 (1.00) |
1 (1.00) |
| Amp Peak 13(16q11 2) | 3 (6%) | 45 |
1 (1.00) |
0.267 (1.00) |
| Amp Peak 14(17q23 1) | 21 (44%) | 27 |
1 (1.00) |
0.77 (1.00) |
| Amp Peak 15(17q25 3) | 21 (44%) | 27 |
0.561 (1.00) |
0.237 (1.00) |
| Del Peak 1(1p36 23) | 21 (44%) | 27 |
1 (1.00) |
0.77 (1.00) |
| Del Peak 2(1p36 13) | 16 (33%) | 32 |
1 (1.00) |
0.759 (1.00) |
| Del Peak 3(2p15) | 5 (10%) | 43 |
0.348 (1.00) |
1 (1.00) |
| Del Peak 4(2q23 1) | 5 (10%) | 43 |
1 (1.00) |
0.142 (1.00) |
| Del Peak 5(2q34) | 6 (12%) | 42 |
1 (1.00) |
0.381 (1.00) |
| Del Peak 6(3p21 1) | 10 (21%) | 38 |
0.724 (1.00) |
0.0363 (1.00) |
| Del Peak 7(3p13) | 9 (19%) | 39 |
0.461 (1.00) |
0.451 (1.00) |
| Del Peak 8(4q22 3) | 18 (38%) | 30 |
1 (1.00) |
0.073 (1.00) |
| Del Peak 9(4q31 3) | 14 (29%) | 34 |
0.752 (1.00) |
0.119 (1.00) |
| Del Peak 10(6q26) | 14 (29%) | 34 |
0.752 (1.00) |
1 (1.00) |
| Del Peak 11(7q33) | 6 (12%) | 42 |
0.666 (1.00) |
0.197 (1.00) |
| Del Peak 12(8p23 2) | 27 (56%) | 21 |
1 (1.00) |
0.38 (1.00) |
| Del Peak 13(9p21 3) | 18 (38%) | 30 |
1 (1.00) |
0.554 (1.00) |
| Del Peak 14(10q23 31) | 16 (33%) | 32 |
0.76 (1.00) |
0.357 (1.00) |
| Del Peak 15(10q24 33) | 14 (29%) | 34 |
1 (1.00) |
1 (1.00) |
| Del Peak 16(11q14 1) | 8 (17%) | 40 |
0.701 (1.00) |
0.451 (1.00) |
| Del Peak 17(13q14 2) | 22 (46%) | 26 |
1 (1.00) |
1 (1.00) |
| Del Peak 18(14q23 3) | 17 (35%) | 31 |
0.0687 (1.00) |
0.762 (1.00) |
| Del Peak 19(15q21 1) | 8 (17%) | 40 |
1 (1.00) |
1 (1.00) |
| Del Peak 20(16q22 3) | 20 (42%) | 28 |
1 (1.00) |
0.245 (1.00) |
| Del Peak 21(17p12) | 26 (54%) | 22 |
0.385 (1.00) |
0.557 (1.00) |
| Del Peak 22(18q12 2) | 9 (19%) | 39 |
1 (1.00) |
1 (1.00) |
| Del Peak 23(19q13 33) | 4 (8%) | 44 |
0.609 (1.00) |
1 (1.00) |
| Del Peak 24(22q12 1) | 9 (19%) | 39 |
0.137 (1.00) |
0.127 (1.00) |
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Copy number data file = All Lesions File (all_lesions.conf_##.txt, where ## is the confidence level). The all lesions file is from GISTIC pipeline and summarizes the results from the GISTIC run. It contains data about the significant regions of amplification and deletion as well as which samples are amplified or deleted in each of these regions. The identified regions are listed down the first column, and the samples are listed across the first row, starting in column 10.
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Clinical data file = LIHC.clin.merged.picked.txt
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Number of patients = 48
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Number of copy number variation regions = 39
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Number of selected clinical features = 2
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Exclude regions that fewer than K tumors have alterations, K = 3
For binary or multi-class clinical features (nominal or ordinal), two-tailed Fisher's exact tests (Fisher 1922) were used to estimate the P values using the 'fisher.test' function in R
For multiple hypothesis correction, Q value is the False Discovery Rate (FDR) analogue of the P value (Benjamini and Hochberg 1995), defined as the minimum FDR at which the test may be called significant. We used the 'Benjamini and Hochberg' method of 'p.adjust' function in R to convert P values into Q values.
This is an experimental feature. The full results of the analysis summarized in this report can be downloaded from the TCGA Data Coordination Center.